« Courbe de validation » : différence entre les versions
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''' Validation Curve''' | ''' Validation Curve''' | ||
The validation curve plots the influence of a single hyperparameter on the train and validation set. By looking at the curve, we can determine the overfitting, underfitting and just-right conditions of the model for the specified values of the given hyperparameter. When there are multiple hyperparameters to tune at once, the validation curve cannot be used. Instated, you can use grid search or random search. | |||
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[https://towardsdatascience.com/10-amazing-machine-learning-visualizations-you-should-know-in-2023-528282940582 Source : towardsdatascience ] | [https://towardsdatascience.com/10-amazing-machine-learning-visualizations-you-should-know-in-2023-528282940582 Source : towardsdatascience ] | ||
[[Catégorie:vocabulary]] | [[Catégorie:vocabulary]] | ||
Version du 7 novembre 2022 à 09:46
en construction
Définition
XXXXXXXXX
Français
XXXXXXXXX
Anglais
Validation Curve
The validation curve plots the influence of a single hyperparameter on the train and validation set. By looking at the curve, we can determine the overfitting, underfitting and just-right conditions of the model for the specified values of the given hyperparameter. When there are multiple hyperparameters to tune at once, the validation curve cannot be used. Instated, you can use grid search or random search.
Contributeurs: Amanda Clément, wiki
